Memory-induced nonlinear dynamics in a fractional human–mosquito malaria model with data-driven insights

Article published in ANNALI DELL'UNIVERSITA' DI FERRARA

Published in Microbiology and Mathematics

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Springer Milan
Springer Milan Springer Milan

Memory-induced nonlinear dynamics in a fractional human–mosquito malaria model with data-driven insights

This study investigates the influence of non-local memory effects on the nonlinear dynamics of malaria transmission using a fractional-order human mosquito model formulated in the Atangana–Baleanu–Caputo (ABC) sense. The model incorporates a non-singular kernel to capture hereditary characteristics inherent in epidemiological processes, with the fractional order acting as a control parameter governing system dynamics. Analytical results establish positivity, boundedness, and the existence of unique solutions, while stability conditions for disease-free and endemic equilibria are derived. Although the classical threshold structure governed by the basic reproduction number is preserved, the inclusion of memory effects produces significant qualitative changes in transient behavior. Specifically, decreasing the fractional order delays epidemic peaks, reduces infection intensity, and yields smoother convergence toward equilibrium, indicating a memory-induced modulation of nonlinear dynamics. Model parameters are calibrated using malaria incidence data from $$2000--2023$$ 2000 - - 2023 , and numerical simulations confirm the robustness of these effects. The findings demonstrate that fractional dynamics fundamentally reshape transient epidemic evolution, providing new insight into memory-driven processes in complex biological systems and nonlinear epidemiological modeling.

Our paper investigates the influence of non-local memory effects on malaria transmission dynamics using a fractional-order human mosquito model in the Atangana–Baleanu–Caputo (ABC) sense. By incorporating a non-singular kernel, we capture the hereditary characteristics of epidemiological processes, with the fractional order serving as a control parameter. Our analytical results confirm positivity, boundedness, and unique solutions, while stability conditions for disease-free and endemic equilibria are derived. Notably, memory effects significantly alter transient behavior, delaying epidemic peaks and reducing infection intensity. These findings offer new insights into memory-driven processes in epidemiological modeling. Read the full paper here.

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Infectious-Disease Epidemiology
Life Sciences > Biological Sciences > Microbiology > Medical Microbiology > Infectious-Disease Epidemiology
Malaria
Life Sciences > Health Sciences > Biomedical Research > Medical Microbiology > Infectious Diseases > Malaria
Computational Mathematics and Numerical Analysis
Mathematics and Computing > Mathematics > Computational Mathematics and Numerical Analysis